developer_uid: RandomForest1024
submission_id: albertwang8192-2025-07-04-0_v1
model_name: 2025-07-04_0
model_group: AlbertWang8192/2025-07-0
status: torndown
timestamp: 2025-07-04T13:35:46+00:00
num_battles: 8655
num_wins: 3890
celo_rating: 1251.2
family_friendly_score: 0.5972
family_friendly_standard_error: 0.006936168394726299
submission_type: basic
model_repo: AlbertWang8192/2025-07-04_0
model_architecture: MistralForCausalLM
model_num_parameters: 12772070400.0
best_of: 8
max_input_tokens: 1024
max_output_tokens: 64
reward_model: default
latencies: [{'batch_size': 1, 'throughput': 0.5980311978532652, 'latency_mean': 1.6720497620105743, 'latency_p50': 1.6756964921951294, 'latency_p90': 1.8397345066070556}, {'batch_size': 3, 'throughput': 1.0769224664307844, 'latency_mean': 2.7725095069408416, 'latency_p50': 2.7871999740600586, 'latency_p90': 3.070440411567688}, {'batch_size': 5, 'throughput': 1.2922639170244918, 'latency_mean': 3.8459019148349762, 'latency_p50': 3.8141661882400513, 'latency_p90': 4.392385625839234}, {'batch_size': 6, 'throughput': 1.351814584627043, 'latency_mean': 4.41522733449936, 'latency_p50': 4.408831238746643, 'latency_p90': 4.944935226440429}, {'batch_size': 8, 'throughput': 1.4183107798108734, 'latency_mean': 5.598518220186233, 'latency_p50': 5.573455452919006, 'latency_p90': 6.316957473754883}, {'batch_size': 10, 'throughput': 1.4566100678188638, 'latency_mean': 6.824962819814682, 'latency_p50': 6.791612982749939, 'latency_p90': 7.645836353302002}]
gpu_counts: {'NVIDIA RTX A5000': 1}
display_name: 2025-07-04_0
is_internal_developer: False
language_model: AlbertWang8192/2025-07-04_0
model_size: 13B
ranking_group: single
throughput_3p7s: 1.28
us_pacific_date: 2025-07-04
win_ratio: 0.4494511842865396
generation_params: {'temperature': 0.6, 'top_p': 0.95, 'min_p': 0.025, 'top_k': 60, 'presence_penalty': 0.4, 'frequency_penalty': 0.4, 'stopping_words': ['\n', '<|im_end|>', '<|im_start|>'], 'max_input_tokens': 1024, 'best_of': 8, 'max_output_tokens': 64}
formatter: {'memory_template': "{bot_name}'s Persona: {memory}\n####\n", 'prompt_template': '{prompt}\n<START>\n', 'bot_template': '{bot_name}: {message}\n', 'user_template': '{user_name}: {message}\n', 'response_template': '{bot_name}:', 'truncate_by_message': False}
Resubmit model
Shutdown handler not registered because Python interpreter is not running in the main thread
run pipeline %s
run pipeline stage %s
Running pipeline stage MKMLizer
Starting job with name albertwang8192-2025-07-04-0-v1-mkmlizer
Waiting for job on albertwang8192-2025-07-04-0-v1-mkmlizer to finish
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albertwang8192-2025-07-04-0-v1-mkmlizer: ║ ║
albertwang8192-2025-07-04-0-v1-mkmlizer: ║ Version: 0.29.15 ║
albertwang8192-2025-07-04-0-v1-mkmlizer: ║ Features: FLYWHEEL, CUDA ║
albertwang8192-2025-07-04-0-v1-mkmlizer: ║ Copyright 2023-2025 MK ONE TECHNOLOGIES Inc. ║
albertwang8192-2025-07-04-0-v1-mkmlizer: ║ https://mk1.ai ║
albertwang8192-2025-07-04-0-v1-mkmlizer: ║ ║
albertwang8192-2025-07-04-0-v1-mkmlizer: ║ The license key for the current software has been verified as ║
albertwang8192-2025-07-04-0-v1-mkmlizer: ║ belonging to: ║
albertwang8192-2025-07-04-0-v1-mkmlizer: ║ ║
albertwang8192-2025-07-04-0-v1-mkmlizer: ║ Chai Research Corp. ║
albertwang8192-2025-07-04-0-v1-mkmlizer: ║ Account ID: 7997a29f-0ceb-4cc7-9adf-840c57b4ae6f ║
albertwang8192-2025-07-04-0-v1-mkmlizer: ║ Expiration: 2028-03-31 23:59:59 ║
albertwang8192-2025-07-04-0-v1-mkmlizer: ║ ║
albertwang8192-2025-07-04-0-v1-mkmlizer: ╚═════════════════════════════════════════════════════════════════════╝
albertwang8192-2025-07-04-0-v1-mkmlizer: Downloaded to shared memory in 40.918s
albertwang8192-2025-07-04-0-v1-mkmlizer: Checking if AlbertWang8192/2025-07-04_0 already exists in ChaiML
albertwang8192-2025-07-04-0-v1-mkmlizer: Creating repo ChaiML/2025-07-04_0 and uploading /tmp/tmp2xp74pqx to it
albertwang8192-2025-07-04-0-v1-mkmlizer: 0%| | 0/6 [00:00<?, ?it/s] 17%|█▋ | 1/6 [00:04<00:24, 5.00s/it] 33%|███▎ | 2/6 [00:08<00:16, 4.24s/it] 50%|█████ | 3/6 [00:16<00:17, 5.78s/it] 67%|██████▋ | 4/6 [00:19<00:09, 4.94s/it] 83%|████████▎ | 5/6 [00:23<00:04, 4.54s/it] 100%|██████████| 6/6 [00:24<00:00, 3.39s/it] 100%|██████████| 6/6 [00:24<00:00, 4.16s/it]
albertwang8192-2025-07-04-0-v1-mkmlizer: quantizing model to /dev/shm/model_cache, profile:s0, folder:/tmp/tmp2xp74pqx, device:0
albertwang8192-2025-07-04-0-v1-mkmlizer: Saving flywheel model at /dev/shm/model_cache
albertwang8192-2025-07-04-0-v1-mkmlizer: quantized model in 30.867s
albertwang8192-2025-07-04-0-v1-mkmlizer: Processed model AlbertWang8192/2025-07-04_0 in 121.661s
albertwang8192-2025-07-04-0-v1-mkmlizer: creating bucket guanaco-mkml-models
albertwang8192-2025-07-04-0-v1-mkmlizer: Bucket 's3://guanaco-mkml-models/' created
albertwang8192-2025-07-04-0-v1-mkmlizer: uploading /dev/shm/model_cache to s3://guanaco-mkml-models/albertwang8192-2025-07-04-0-v1/nvidia
albertwang8192-2025-07-04-0-v1-mkmlizer: cp /dev/shm/model_cache/config.json s3://guanaco-mkml-models/albertwang8192-2025-07-04-0-v1/nvidia/config.json
albertwang8192-2025-07-04-0-v1-mkmlizer: cp /dev/shm/model_cache/special_tokens_map.json s3://guanaco-mkml-models/albertwang8192-2025-07-04-0-v1/nvidia/special_tokens_map.json
albertwang8192-2025-07-04-0-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer_config.json s3://guanaco-mkml-models/albertwang8192-2025-07-04-0-v1/nvidia/tokenizer_config.json
albertwang8192-2025-07-04-0-v1-mkmlizer: cp /dev/shm/model_cache/tokenizer.json s3://guanaco-mkml-models/albertwang8192-2025-07-04-0-v1/nvidia/tokenizer.json
albertwang8192-2025-07-04-0-v1-mkmlizer: cp /dev/shm/model_cache/flywheel_model.0.safetensors s3://guanaco-mkml-models/albertwang8192-2025-07-04-0-v1/nvidia/flywheel_model.0.safetensors
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Job albertwang8192-2025-07-04-0-v1-mkmlizer completed after 145.83s with status: succeeded
Stopping job with name albertwang8192-2025-07-04-0-v1-mkmlizer
Pipeline stage MKMLizer completed in 146.37s
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Running pipeline stage MKMLTemplater
Pipeline stage MKMLTemplater completed in 0.16s
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Running pipeline stage MKMLDeployer
Creating inference service albertwang8192-2025-07-04-0-v1
Waiting for inference service albertwang8192-2025-07-04-0-v1 to be ready
Inference service albertwang8192-2025-07-04-0-v1 ready after 220.80756044387817s
Pipeline stage MKMLDeployer completed in 221.67s
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Running pipeline stage StressChecker
Received healthy response to inference request in 2.4337291717529297s
Received healthy response to inference request in 1.7509653568267822s
Received healthy response to inference request in 1.5410821437835693s
Received healthy response to inference request in 2.2177131175994873s
Received healthy response to inference request in 1.5971972942352295s
5 requests
0 failed requests
5th percentile: 1.5523051738739013
10th percentile: 1.5635282039642333
20th percentile: 1.5859742641448975
30th percentile: 1.62795090675354
40th percentile: 1.6894581317901611
50th percentile: 1.7509653568267822
60th percentile: 1.9376644611358642
70th percentile: 2.124363565444946
80th percentile: 2.260916328430176
90th percentile: 2.3473227500915526
95th percentile: 2.390525960922241
99th percentile: 2.425088529586792
mean time: 1.9081374168395997
Pipeline stage StressChecker completed in 11.15s
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Pipeline stage TriggerMKMLProfilingPipeline completed in 0.78s
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Evaluating %s Family Friendly Score with %s threads
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Evaluating %s Family Friendly Score with %s threads
Pipeline stage OfflineFamilyFriendlyScorer completed in 5392.79s
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albertwang8192-2025-07-04-0_v1 status is now torndown due to DeploymentManager action